SUPPLEMENTARY INFORMATION

Transcription

1 SUPPLEMENTARY INFORMATION Spatially variable response of Himalayan glaciers to climate change affected by debris cover Dirk Scherler 1 *, Bodo Bookhagen 2, Manfred R. Strecker 1 1 Institute of Earth and Environmental Science, University Potsdam, Karl- Liebknecht-Str. 24, Potsdam, Germany 2 Department of Geography, 1832 Ellison Hall, University of California Santa Barbara, Santa Barbara, CA * dirk@geo.uni-potsdam.de In this document, we provide additional details on our methodological approach, including characteristic examples for the glacier analysis (Figures S1-S3). In Figure S4, we show the precipitation data that we used for simple modelling of the climate sensitivity and response time of the studied glaciers, which is shown in Figure S5. We furthermore provide details on the satellite images that were used for obtaining glacier-surface velocities (Tables S1-S2) and for measuring debris-covered glacier areas (Table S3). In addition, we list details on the results of the image correlations, which form the basis for measuring glacier-surface velocities (Table S4). In Table S5, we list all relevant results that we obtained for each of the studied glaciers. nature geoscience 1

2 supplementary information Glacier-surface velocities Obtaining glacier-surface velocities from optical satellite imagery is a well established method 1-6. However, when studying alpine glaciers, typical measurement uncertainties are approximately one pixel of the satellite image. We used the program COSI-Corr 6 for precise orthorectification, co-registration, and sub-pixel correlation of ASTER and SPOT satellite images from 2000 to 2008 (Table S1-S2) and followed the procedures outlined in ref. 7 to obtain accurate surface velocities. We analyzed glacier-surface velocities within twelve heavily ice-covered areas in the greater Himalayan realm and studied any glacier within these areas with enough data coverage to construct a velocity profile along the trunk glacier without significant data gaps. We excluded surging glaciers from our analysis, which alternate between usually rapid advances and longer periods of slow retreat and/or stability. We identified such glaciers from distorted medial moraines 8. Surface velocities were obtained along the central flowline of the studied glaciers, which we identified manually, based on the satellite images and the velocity maps (Figure S1). We measured the proportion of the velocity profile extending upstream from the terminus with velocities <2.5 m yr -1 as an indicator of quasi-stagnant ice (Figure S2). This particular threshold is guided by the average uncertainties in the velocity measurements, which we calculated from the correlation uncertainties, and the associated limitations in discriminating between moving and stagnant ice (Table S4). We tested higher and lower thresholds (0-5 m yr -1 ), but these mostly shift the statistical moments of the distributions to higher and lower fractions, respectively, without producing effects on the relative differences. The temporal separation of the satellite images is generally close to an integer multiple of one year (Table S4) and thus not biased by seasonal velocity variations 7. Each profile is constructed from 2 nature geoscience

3 supplementary information several measurements and final velocities reflect mean annual velocities averaged over the years or a shorter time span. Debris cover The extent of debris cover was determined based on digitized glacier outlines combined with the distribution of clean ice and snow at the end of the hydrological year, obtained from Landsat Thematic Mapper (TM) band TM4/TM5-ratio images 9 (Figure S1, Table S3). The effect of debris cover on melt rates is well known 10,11, and several studies have quantified the relationship between debris thickness and melt rate At a debris thickness of less than ~2-4 cm, the albedo effect dominates and ice melting accelerates, whereas at a debris thickness of more than ~2-4 cm, the insulation effect dominates and melt rates are lower compared to clean ice. It is presently impossible to quantify debris-cover thickness reliably using remote-sensing methods. However, ground-based studies report common debris-cover thicknesses of cm 12-17, indicating that the insulating effect of debris cover on melt rates may be substantial on some Himalayan glaciers. The percentage of debris cover (by area) on the studied glaciers is unrelated to the size of the glaciers in each of the study regions (Figure S3). Hence, regional differences in the size distribution of the studied glaciers do not affect our results. Glacier frontal changes We measured changes in glacier area at the terminus from the earliest and latest suitable orthorectified 15-m resolution ASTER images that were used for the velocity measurements. Combined with glacier widths we calculated mean annual advance or retreat rates during the period of investigation. For most of the glaciers, suitable nature geoscience 3

4 supplementary information scenes separated by at least four years are available and allow determination of frontal changes during the observation period (Table S5). Identifying the edges of debris-covered glaciers is not possible by standard ice and snow mapping techniques, and despite efforts using automatic mapping 9, the most accurate procedure is still manual delineation by one expert investigator 18. In our study, the high number of accurately co-registered satellite images facilitates detection of surface-area changes. Following ref. 18, we estimated mapping inaccuracies by comparing several ASTER-based area changes with those obtained from 5-m resolution SPOT images. Although the periods between the available images are not identical, deviations of mean annual frontal changes are on average ~5 m yr -1, and up to ~20 m yr -1 in the case of one heavily debris-covered glacier. For this study, we assume a uniform uncertainty of ~10 m yr -1 for all studied glaciers, which is likely a conservative estimate. DEM analysis We estimated the snowline elevation, using orthorectified satellite images (ASTER, SPOT, Landsat ETM+) that were acquired near the end of the hydrological year, when snow cover is lowest 19. We manually determined the surface elevation at the boundary between bright snow and darker ice using a void-filled SRTM based digital elevation model (DEM) 20. Snowline elevations vary between years and different aspects on any one glacier by m. For this study, we used the ELA estimates to calculate mean slope angles in the accumulation areas, i.e., all catchment areas of a glacier that lie above the ELA. The DEM has a spatial resolution of ~90 m and a vertical accuracy better than 16 m 21. Inaccuracies in measured slope angles due to DEM resolution and accuracy are greater for steeper slope angles, but generally unimportant for the purpose of our study. We measured the slope of the ice surface in 4 nature geoscience

5 supplementary information the terminus regions of the studied glaciers along our profiles that follow the central flowline. We calculated mean surface slopes along a distance of 1 km or 2 km upstream from the terminus of glaciers with 5 km and >5 km length, respectively. It should be noted that the DEM of ref. 20 has the SRTM-voids filled using, amongst others, Soviet military topographic maps, which date as far back as the 1970 s. The possible glacier-surface lowering of some metres between this time and February 2000, when the SRTM DEM has been acquired is unlikely to be significant for the present purpose for three reasons. First, the void-filling is based on converting the SRTM DEM into contour lines, closing the voids by tracing the contours from the topographic maps, converting back to a raster-dem and using this surface as a source to fill the void. Hence, the voids have been filled with relative, not absolute elevation data. Second, the SRTM data is largely void-free over gentle sloping glacier surfaces. Second, potential elevation changes do not significantly distort the orthorectified near-nadir 3N band ASTER images. Therefore our velocity measurements at the gentle sloping lower parts of glaciers are unaffected by this potential bias. nature geoscience 5

6 supplementary information Figure S1: Example of glacier analysis and data from the Mt. Everest region, Nepal. (a) Orthorectified ASTER-satellite images (3N band) from November Red polygons delineate the studied glaciers. (b) Velocity map derived from correlation of the image in A with images from November Only velocities >2.5 m yr -1 are shown. Black line gives trace of profile in Figure S2. (c) Distribution of debris cover derived from combination of mapped glacier extents with Landsat band TM4/TM5-ratio threshold images. (d) Distribution of quasi-stagnant ice, i.e. parts of the glaciers moving at <2.5 m yr -1. (e) Example of a debris-covered glacier (Ngojumba Glacier, Khumbu Himal, Nepal), which shows no sign of retreat. (f) Example of a debris-free glacier, with an average retreat rate of ~31 m yr -1 between December 2000 and January 2008 (unknown glacier name, Manaslu Himal, Nepal). 6 nature geoscience

7 supplementary information Figure S2: Example of glacier-surface velocities and stagnating terminus region. (a) Surface elevation (black) and slope (red) along the profile from Khumbu Glacier (see Figure S1 for location). (b) Mean annual surface-velocity (red line), based on a large number of individual measurements (black crosses) between 2000 and Light-grey polygon in background gives number of velocity measurements per profile point (y-axis on the left side). Velocities at a steep portion (Khumbu Icefall) in the central part of the glacier, between km 6 and 8, are less well constrained, but this part is not relevant for our study. (c) Subset of the velocity in the lower 5.5 km of the glacier. Turquoise area at bottom covers velocities <2.5 m yr -1. Dark-grey box indicates mean velocities <2.5 m yr -1. The lower ~2.3 km of this glacier are quasi stagnant. nature geoscience 7

8 supplementary information Figure S3: Regional distribution of glacier sizes and debris-covered areas. Glacier areas versus debris-covered glacier areas for all studied glaciers in the six geographic regions, Hindu Kush (HK), Karakoram (K), western Himalaya (WH), southern central Himalaya (CHS), northern central Himalaya (CHN), and West Kunlun Shan (WKS). Colour-coding depicts areal fraction of debris cover. Redoutlined data points represent glaciers with >20% debris cover. 8 nature geoscience

9 supplementary information Figure S4: Annual precipitation in the study area. Annual precipitation data from Cllimate Research unit (CRU) 2.0 data set 22, with 10-arc minutes horizontal resolution. Note that due to the scarcity of meteorological stations at high altitudes and in remote areas, particularly in the Karakoram and West Kunlun Shan, the actual annual precipitation may not be depicted correctly. However, the general pattern is identical with other gridded and station-based climatologies. nature geoscience 9

10 supplementary information Figure S5: Modelled climate sensitivities (a, c) and response times (b, d) of the studied glaciers. Upper panels (a, b) show data points coloured by geographic region, lower panels show data points coloured by debris cover (in % by area). We modelled climate sensitivity (c) and response time (τ) for each glacier using equations given in ref. 23 and updated in ref. 24: c = c 1 P 0.5 s -1 and τ = c 2 ß -1 s -1 (1 + 20s) -0.5 L -0.5, with ß = P 0.5. Here, s is the mean surface slope of the glacier, L is glacier length, ß is the balance gradient, and P is the mean annual precipitation (in m yr -1 ), derived from the CRU 2.0 data set (see Figure S4). c 1 and c 2 are constants that have been calibrated with results from numerical glacier models and take the values 430 and 17.9 (ref. 24). No systematic patterns in response times or climate sensitivities can be observed that could potentially explain the observed discrepancies in frontal change rates. 10 nature geoscience

11 supplementary information In the following tables, the geographic regions (if indicated) are part of the main regions that are mentioned in the text. Note that we distinguished glaciers in the central Himalaya based on their position with respect to the topographic divide between the Himalaya to the south and the Tibetan Plateau to the north (see text for details). Hindu Kush (HK): Chitral (south), Chitral (north) Karakoram (K): Hispar, Biafo Gyang, Baltoro Western Himalaya (WH): Jammu, Lahul (south), Lahul (north) Central Himalaya (CH): Bhutan, Kanchenjunga, Khumbu, Manaslu, Gurla Mandatha, Garhwal (Gangotri), Garhwal (Tons), Leo Pargil West Kunlun Shan (WKS): West Kunlun Shan nature geoscience 11

12 supplementary information Table S1: List of all ASTER satellite images used in this study. No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 1 Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Bhutan ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Kanchenjunga ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A nature geoscience

13 supplementary information No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 63 Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Khumbu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Manaslu ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Gurla Mandatha ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A nature geoscience 13

14 supplementary information No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 131 Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Gangotri) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Garhwal (Tons) ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Leo Pargil ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (South) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A nature geoscience

15 supplementary information No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 199 Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Lahul (North) ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Jammu ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Baltoro) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A nature geoscience 15

16 supplementary information No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 267 Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Biafo Gyang) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Karakoram (Hispar) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (North) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A Hindu Kush (South) ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A nature geoscience

17 supplementary information No. Geographic region ASTER Granule ID Acquisition date (dd.mm.yyyy) Incidence angle ( ) Cloud cover (%) 335 West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A West Kunlun Shan ASTL1A Percentage cloud cover during image acquisition is provided in the metadata of the ASTER images, but, to our experience, is usually overestimated. nature geoscience 17

18 supplementary information Table S2: List of all SPOT satellite images used in this study. Instrument and Sensor Processing level Column (K) Row (J) Date (dd.mm.yyyy) Incidence angle ( ) SPOT 4 HRVIR 1 L1A SPOT 5 HRG 1 L1A SPOT 5 HRG 1 L1A SPOT 5 HRG 2 L1A SPOT 5 HRG 2 L1A SPOT 5 HRG 1 L1A Table S3: List of all LANDSAT satellite images used in this study. Instrument and Sensor Processing level Path Row Date (dd.mm.yyyy) LANDSAT 5 TM Orthorectified LANDSAT 5 TM Orthorectified LANDSAT 5 TM Orthorectified LANDSAT 5 TM Orthorectified LANDSAT 5 TM Orthorectified LANDSAT 5 TM Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified LANDSAT 7 ETM+ Orthorectified nature geoscience

19 supplementary information Table S4: Image correlation details. No. Geographic region Date (dd.mm.yyyy) Scene 1 Scene 2 Time span (yr) Incidence (m) uncertainty (m) uncertainty Image-cross correlation residual offset Total displacement Velocity angle East-West North-South (m yr -1 ) diff. ( ) Mean SD Mean SD Mean SD Mean SD 1 Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Bhutan Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga nature geoscience 19

20 supplementary information No. Geographic region Date (dd.mm.yyyy) Scene 1 Scene 2 Time span (yr) Incidence (m) uncertainty (m) uncertainty Image-cross correlation residual offset Total displacement Velocity angle East-West North-South (m yr -1 ) diff. ( ) Mean SD Mean SD Mean SD Mean SD 62 Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Kanchenjunga Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) Khumbu (South) nature geoscience